Robotic lower-limb prosthesis is an emerging technology which has been developed since the decades from the end of the 20th century to the beginning of the 21st century. Robotic lower-limb prosthesis is usually equipped with the specialized control system and the particularly designed mechanical structure. These characteristics allow it to accurately mimic human joint angle curves and to restore the joint torques during ambulation, both of which greatly extents the walking ability of the lower extremity amputees. At the current stage, the most common control strategy for the robotic prosthesis is the hierarchical control, wherein the high level controller recognizes the locomotion modes on different terrains such as level walking, stair ascending, etc. The middle level controller derivates the angle curves and the torque curves based on the corresponding locomotion mode. The low level controller drives the actuation system (including motors, hydraulic system, and pneumatic system) to achieve the human joint dynamics.
The sensing system and sensing strategy are crucial for accurate and timely recognition of human motion information, which is the primary goal of the hierarchical control system. At the current stage of this field, the most widely applied technology is the surface electromyography (sEMG) based sensing system. The sEMG signal exhibits short time latency and accurate motion information, as it directly records muscle contraction information. However, in the application of lower-limb prosthesis, there exist some limitations using sEMG sensing systems. First, in order to record useful muscle signals, the sEMG electrode has to be placed at the position of the measured muscle. Due to the amputation, the muscle loss on the limb and the residual muscle atrophy make it difficult to sample enough channels of sEMG signals. Second, the sEMG electrodes are tightly adhered to the skin, and thereby the pressures on the sensing spots made by the electrodes will cause skin damage and pressure sores, especially in long time use. Meanwhile, the sweats impact on the signal quality and decrease the system's performance. Third, sEMG signal is weak in magnitude (dozens of microvolt) and the valid frequency ranges from several Hz to 1 kHz. To digitally sample the signals, multi-stage amplifiers and filters are needed in the sampling circuits. The complication of the sampling circuits increases the cost of the whole system, especially for multi-channel sampling.
At present, the current capacitive sensing technology for recognizing locomotion modes records the muscle shape changes on the leg based on the particularly designed sensing bands. This technology is a potential alternative to EMG based system in locomotion mode recognition, and it is promising in applications of exoskeleton control and human motion detection. However, for lower-limb prosthesis, there exist some limitations. First, the electrodes on the sensing bands directly contact with the skin, in which condition, the sweats still potentially impacts on the performance. Second, the electrode positions have to be configured each time re-wearing the bands, which increase the inconvenience in daily application. Third, for lower extremity amputees, sensing bands cannot be placed inside the socket. As a result, for transtibial amputees, only the band on the thigh can be used, and the transfemoral amputees cannot use it due to the limited residual limb length.